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Novelis Research
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Targeted re-decoding can boost accuracy by up to 4.5 percentage points in quantized small language models, revealing a selective repair mechanism for problematic inference trajectories.
Centered token log-probability fails as a reliable monitor for reasoning models, but a new calibrated decoding controller enhances detection of unreliable outputs without extensive retraining.